# How Gendered is the Peer Review Process? A Mixed-Design Analysis of Reviewer Feedback

Thomas König
Guido Ropers

## Overview

The reproduction material contains three data sets which allow to reproduce the results presented in the paper and supplemental information. The files are located in the 01_data folder. To reproduce the analysis, you need to run the master R script called 00_master.R. It loads the data and executes additional code files in the 00_script folder to create the output figures and tables from the manuscript and the supplemental information. The output is stored in a corresponding folder called 02_output.

## Data

1. manuscript_data.csv
	+ manuscript_id: Pseudonymized manuscript ID
	+ first_decision: First decicion term 
	+ gender_type: Authorship gender type (*Male Solo, Female Solo, Male Team, Female Team, Mixed Team*)
	+ gender_type3: Aggregated authorship type (*Male, Female, Mixed Team*)
    + n_gender: Number of different author gender (*[1,2]*)
    + n_authors Number of authors
    + n_complete_reviewers: Number of completed reviews

2. reviewer_data.csv
    + manuscript_id: Pseudonymized manuscript ID
    + first_decision: First decicion term 
    + recommendation: Reviewer recommendation (*Accept, Minor Revisions, Major Revisions, Reject*)
    + pos_rec: Non-reject recommendation
    + subfield: Subfield as stored in Editorial Manager
    + gender_type: Authorship gender type (*Male Solo, Female Solo, Male Team, Female Team, Mixed Team*)
    + gender_type3: Aggregated authorship type (*Male, Female, Mixed Team*)
    + r_gender: Reviewer gender (*female, male*)
    + Female: Female reviewer (dummy)
    + fem_r: Female reviewer (dummy)
    + male_r: Male reviewer (dummy)
    + n_referees: Number of reviewers per manuscript
    + missing_comment: No written report was uploaded to Editorial Manager
    + missing_sentiment: Sentiment score is missing
    + wordcount_adj: Word count reviewer report
    + positive: Number of positive words (based on NRC dictionary)
    + negative: Number of negative words (based on NRC dictionary)
    + sentimentscore: positive-negative
    + disgust: Number of words connotated with disgust (based on NRC dictionary)
    + duration: Review duration (days with reviewer)
    + obs_id: observation ID

3.  reviewer_invitations_data.csv
    + obs_id_invites: observation ID (for privacy reasons, it does not match the one in reviewer_data.csv)
    + r_gender: Reviewer gender (*female, male*)
    + manuscript_id: Pseudonymized manuscript ID


